MCP Toolz

mcp-name: io.github.taylorleese/mcp-toolz

MCP server for Claude Code that provides multi-LLM feedback tools.

Features

• Multi-LLM Feedback: Get second opinions from ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), and DeepSeek
• MCP Integration: Works with Claude Code via the Model Context Protocol

Quick Start

Installation

From PyPI (Recommended)

pip install mcp-toolz

From Source (Development)

# Clone the repository
git clone https://github.com/taylorleese/mcp-toolz.git
cd mcp-toolz

# Create and activate virtual environment
python3 -m venv venv
source venv/bin/activate  # macOS/Linux
# or: venv\Scripts\activate  # Windows

# Install in editable mode with dev dependencies
pip install -e ".[dev]"

Configuration

# Set your API keys as environment variables (at least one required for AI feedback tools)
export OPENAI_API_KEY=sk-...           # For ChatGPT
export ANTHROPIC_API_KEY=sk-ant-...    # For Claude
export GOOGLE_API_KEY=...              # For Gemini
export DEEPSEEK_API_KEY=sk-...         # For DeepSeek

# Or create a .env file (if installing from source)
cp .env.example .env
# Edit .env and add your API keys

MCP Server Setup

Add to your Claude Code MCP settings:

If installed via pip:

{
  "mcpServers": {
    "mcp-toolz": {
      "command": "python",
      "args": ["-m", "mcp_server"],
      "env": {
        "OPENAI_API_KEY": "sk-...",
        "ANTHROPIC_API_KEY": "sk-ant-...",
        "GOOGLE_API_KEY": "...",
        "DEEPSEEK_API_KEY": "sk-..."
      }
    }
  }
}

If installed from source:

{
  "mcpServers": {
    "mcp-toolz": {
      "command": "python",
      "args": ["-m", "mcp_server"],
      "cwd": "/absolute/path/to/mcp-toolz",
      "env": {
        "PYTHONPATH": "/absolute/path/to/mcp-toolz/src"
      }
    }
  }
}

Restart Claude Code to load the MCP server.

MCP Server Tools

AI Feedback Tools

Get second opinions from multiple LLMs on code, architecture decisions, and implementation plans:

• ask_chatgpt - Get ChatGPT's analysis (supports custom questions)
• ask_claude - Get Claude's analysis (supports custom questions)
• ask_gemini - Get Gemini's analysis (supports custom questions)
• ask_deepseek - Get DeepSeek's analysis (supports custom questions)

Claude Code Skills

/resolve-github-alerts

Automatically triages and resolves GitHub security alerts (Dependabot, code scanning, secret scanning). Run it in Claude Code to:

• Fix failing Dependabot PRs (lint/test issues)
• Bump vulnerable dependencies and recompile requirements
• Remediate code scanning and secret scanning alerts
• Submit a single PR with all fixes for manual review

/resolve-github-alerts

Usage Examples

Get Multiple AI Perspectives

I'm deciding between Redis and Memcached for caching user sessions.
Ask ChatGPT for their analysis.

Follow up with:

• "Ask Claude the same question for comparison"
• "Ask Gemini for another perspective"
• "What does DeepSeek think about this?"

Debug with Multiple Perspectives

I'm getting "TypeError: Cannot read property 'map' of undefined" in my React component.
The error occurs in UserList.jsx when rendering the users array.
Ask ChatGPT and Claude for debugging suggestions.

Environment Variables

# Required (at least one for AI feedback tools)
OPENAI_API_KEY=sk-...                              # Your OpenAI API key
ANTHROPIC_API_KEY=sk-ant-...                       # Your Anthropic API key
GOOGLE_API_KEY=...                                 # Your Google API key (for Gemini)
DEEPSEEK_API_KEY=sk-...                            # Your DeepSeek API key

# Optional
MCP_TOOLZ_MODEL=gpt-5                                         # OpenAI model (default: gpt-5)
MCP_TOOLZ_CLAUDE_MODEL=claude-sonnet-4-5-20250929             # Claude model
MCP_TOOLZ_GEMINI_MODEL=gemini-2.0-flash-thinking-exp-01-21   # Gemini model
MCP_TOOLZ_DEEPSEEK_MODEL=deepseek-chat                        # DeepSeek model

Troubleshooting

"Error 401: Invalid API key"

• Verify API keys are set in .env or environment variables
• Check billing is enabled on your API provider account

"No module named context_manager"

• Use PYTHONPATH=src before running Python directly
• Or install via pip: pip install mcp-toolz

Project Structure

mcp-toolz/
├── src/
│   ├── mcp_server/              # MCP server for Claude Code
│   │   └── server.py            # MCP tools and handlers
│   └── context_manager/         # Client implementations
│       ├── openai_client.py     # ChatGPT API client
│       ├── anthropic_client.py  # Claude API client
│       ├── gemini_client.py     # Gemini API client
│       └── deepseek_client.py   # DeepSeek API client
├── tests/                       # pytest tests
├── requirements.in
└── requirements.txt

Development

Setup for Contributors

# Clone and install
git clone https://github.com/taylorleese/mcp-toolz.git
cd mcp-toolz
python3 -m venv venv
source venv/bin/activate
pip install -r requirements-dev.txt

# Install pre-commit hooks (IMPORTANT!)
pre-commit install

# Copy and configure .env
cp .env.example .env
# Edit .env with your API keys

Running Tests

source venv/bin/activate
pytest

Code Quality

# Run all checks (runs automatically on commit after pre-commit install)
pre-commit run --all-files

# Individual tools
black .
ruff check .
mypy src/

License

MIT